RH-AI-STEM

Pre-requisites on an empty MacOS

Install brew:
- /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
Install pip, Cython, wget:
- brew install pip
- brew install wget
- brew install python3
Install virtualenv, Python3:
- $ python3 -m venv ./venv
- $ source ./venv/bin/activate
Install Cython:
- pip install Cython

Setting up environments

Clone this directory to somewhere you like
Run the command:
- source env.sh

Traning Corgi models

Traning:
- $ cd models/research/object_detection
- $ python model_main.py --logtostderr --model_dir=corgi_training/ --pipeline_config_path=corgi_training/corgi.config
Export inference graph:
- TODO: Looking for highest number of trained model in models/research/object_detection/corgi_training
- $ python export_inference_graph.py --input_type image_tensor --pipeline_config_path corgi_training/corgi.config --trained_checkpoint_prefix corgi_training/model.ckpt-<highest_number> --output_directory inference_graph_corgi

Run testing

Copy testing script into tensorflow models:
- $ cd ../../..
- $ cp corgi_detection.py models/research
Run:
- $ python models/research/corgi_detection.py

Notes:

Change the backend of matplotlib in corgi_detection.py to a relevant one of running machine in order to using matplotlib for image rendering